A FRUCTful journey

So, the FRUCT25 conference is done, and with that, presumably my last appearance at an international conference during my MSCA fellowship. My itinerary for the remaining time is pretty straightforward: a month in Dublin, then to Finland again to celebrate Christmas and New Year, then back to Dublin for another month and then it’s a wrap. No more conference papers, time to turn my attention to writing journal articles and final reports.

Considering how many times I’ve landed at Helsinki airport in the recent past, it was a little bit strange to realise that it had been over a year since I last visited the actual city. Despite this being November, hardly a time when anywhere in Finland is at its best, it felt nice to be walking the streets of my country’s capital again. I’ve never lived there, but I’ve spent plenty of time there and it feels very familiar to me, almost like a second home – or perhaps a third one, now that Dublin has been my second home in a very real sense for the past couple of years.

The main reason why I like to visit Helsinki regularly is that quite a few of my friends have ended up living there over the years, and I made sure to reserve plenty of time for seeing them. Normally on a conference trip I would do some touristy things, but in this particular case I felt little need to go sightseeing, although I did scout out some bars and restaurants in advance so I could go check out some interesting ones that I hadn’t tried before. On the flip side of having such easy access to my usual social circles, I also didn’t feel much of an urge to socialise with my fellow conference delegates, although I did have a pleasant chat with a few of them over some wine and snacks at the combined social event and poster/demo session.

The conference itself was a rather low-key and low-budget affair in comparison with the lavish IEEE CEC, but the scientific programme was solid enough, the proceedings will be available on IEEE Xplore and the event is recognised by various national rating systems as a perfectly respectable one. The full title of the conference is “Conference of Open Innovations Association FRUCT”, and it doesn’t really have an easy-to-define theme apart from innovation involving information and communication technologies. FRUCT itself stands for “Finnish-Russian University Cooperation in Telecommunications”, and there is a certain degree of geographical theming in the sense that the events normally alternate between Finnish and Russian locations and most of the participants tend to come from these two countries. However, at least in Helsinki there were delegates also from various other parts of Europe and Asia; according to the official facts and figures, the total number of countries represented by the authors of accepted papers between them was 28.

Shortly before travelling to Finland I sent out an ad looking for volunteers to join the trial I’m running to test the results of the work I’ve done in Dublin. This resulted in a rather busy period as quite a few people were eager to sign up and I needed to get everyone to give their informed consent and start collecting data before I went away. Now that I’m back I find myself in a bit of a lull, since the data collection phase doesn’t require much active involvement from me. This gives me time to do things that are not so central to the success of my project, such as writing this blog and reviewing papers for a 2020 conference I’m in the programme committee of. I also reprised my guest lecturer role from last year, since I was invited to do so by a colleague and I only needed to make some very slight revisions to the slides I used in my previous lecture.

This relatively quiet period won’t last forever, of course. When the data from the trial starts to roll in I’m surely going to have my hands full, so I have no doubt that when I start my end-of-year break, I will do so with a feeling that I really deserve it. Meanwhile, things are already getting busy with my main extracurricular activity, the DCU Campus Choir. Our Christmas concert is approaching fast, with only three regular rehearsals left before it, so we have some extra ones booked and there’s also a fair amount of homework to do. The concert will be in All Hallows Chapel on Monday the 9th of December starting at 19:30, with ~~free admission~~tickets just €5 and followed by a mulled wine and mince pie reception. Do join us if you’re in Dublin!

Rule of three

I recently got a paper accepted to the 25th FRUCT conference in Helsinki, around the same time that another one was published at the 16th CDVE conference in Mallorca, presented by my co-author and co-PI Alan. With the one I presented in Wellington in June, that makes three, not counting the one I gave a talk on in the PAP workshop at last year’s ECML-PKDD in Dublin. The latter didn’t appear in the workshop post-proceedings because of the preliminary nature of the results discussed in it, so it doesn’t really count as a proper publication.

There’s something pleasing about that number three; it makes me feel like I’ve crossed some kind of threshold here. It is, of course, traditionally a very special number, appearing over and over in the stories we tell, the speeches we give, the designs we create… That list right there is a case in point – giving just two examples wouldn’t have been enough, whereas adding a fourth would have been superfluous. There seems to be something inherently satisfying about it when significant things come in threes.

For me, the special significance of this particular three is that it’s been quite a while since I was last able to concentrate on a single research topic long enough to produce several publications on it. In the years following my doctoral graduation, and to some extent even before it, I had a few false starts, working on projects that were good learning experiences for me but in all honesty would probably have been better handled by someone with less learning to do. Sometimes these efforts resulted in one-off papers, sometimes not even that, and none of this was giving me a real sense of advancing either my own career or my field of research.

Against this background, when I started my current project it was potentially yet another false start for me, another new research topic to eventually file under “well, it was worth a shot”. There was a key difference though – this time I had won the funding for the research in my own name and with my own idea. I therefore felt more acutely than usual the need to prove that I’m worthy of such an investment, both to myself and to the funder. This, together with the knowledge that for the next two years I would be working on my own project and nothing else, helped me achieve a depth of commitment that had mostly eluded me between finishing my dissertation and being awarded the MSCA fellowship.

So, the reason for this sense of accomplishment is that while a paper or two can easily be dismissed as a fluke, three has the makings of a pattern: looks like I really am onto something here. It’s not that three papers is enough to make me happy about the results of the project, and I’m certainly not going to have much time for resting on laurels during these last few months, but it’s a welcome boost of confidence, telling me that there probably will be more publications and, further down the line, perhaps more funding as well. I’m no stranger to the impostor syndrome, so especially after a prolonged unproductive period it’s good to get some evidence that maybe I actually am sort of competent at what I do.

There is also another, rather more banal reason why I’m happy that the latest paper got accepted to this particular conference. Had it been rejected, I presume that eventually it would have been accepted somewhere else, but my project will end on 31 January and almost certainly the next opportunity to publish would have been sometime after that date. FRUCT is thus pretty much my last chance to spend the money in my expense budget, and even after that there’s going to be a fairly hefty surplus. Besides, while Helsinki in November may not be the most exotic or enticing travel destination, I have lots of friends there that I very much look forward to catching up with, and I’m also going to take a short holiday to visit home for a few days.

As my time in Ireland approaches its inevitable end, I’m determined to make the best of what’s left of it by exploring places near me, relatively speaking. Last weekend I visited Limerick city, and for the upcoming bank holiday weekend I’m hopping over to Edinburgh to see one of my favourite bands live at Queen’s Hall. Once I’m back from Scotland, I’m away to Finland almost immediately, and once I’m back from there we’ll be well into November already. I’ll probably want to take a little break from travelling after that, but I’d still like to make at least one more weekend trip before I go home for Christmas. I haven’t been to the northwest of the island yet – Sligo might be nice?

Now what?

The September call of the Academy of Finland closed this week; I submitted my application for the Research Fellow grant, and I must admit I’m having mixed feelings about it. Obviously, I’m relieved to have finished the proposal on time and happy to have a work-free weekend ahead of me for a change, but beneath the pleasure of a well-earned rest there are definite undertones of “meh”. Considering the next stage of my career, getting the fellowship would be quite a big deal – the prospect of €5k per month for my own salary for five years plus up to €400k for research expenses is certainly nothing to sneer at – so why doesn’t it feel that way to me?

I guess part of the reason is that you always tend to feel a bit empty after finishing an effort like this, in a dull, “now what?” sort of way. There’s also the fact that I’m simply tired from the final push: it’s not easy to get excited about anything when you feel like you’ve done a week’s worth of work in half the time and then worked another half-week on top of that. Anyway, the funding decisions aren’t due until sometime next spring, so there’s hardly much point in getting excited now – not to mention that statistically, it’s not very likely that I’ll get the grant, so it’s not exactly a rock-solid foundation to base my plans for the future upon.

The slim odds are a big part of why, for quite a long time, I found it hard to drum up any sort of enthusiasm in myself for getting to work on the proposal. Of course, by putting it off I probably just managed to make my chances even slimmer – there was no time to have my application looked at by anyone else, and very little time even for myself to do any substantial rewrites. As a result of this, I don’t know if I can honestly say that I did my best, but I guess I did what I could in the time I gave myself to do it, and of course it’s always the case that you have to strike a balance between such things and everything else going on in your life.

So yeah, it all comes down to priorities ultimately: sure, the fellowship would be a really nice thing to get and I’m sure I’ll be enormously excited if I do get it, but I find that I don’t want it badly enough to have everything else I care about take a back seat for weeks on end. After all, there’s always next year, and then I’ll have a draft proposal to build on, presumably some useful feedback from the review panel, and also plenty of time to get further feedback from the people at the university whose job it is to help researchers prepare applications. Refereeing is always a bit of a crapshoot anyway, sometimes you get lucky with who’s assigned the task of judging your worthiness and sometimes you don’t.

Besides, the quality of the proposal isn’t even the most important criterion in this call – it’s the qualifications of the applicant, so there’s only so much I could have accomplished by putting more hours into perfecting the proposal. By the next call I’ll have wrapped up KDD-CHASER, which means I’ll have more preliminary results and hopefully more publications as well, so that will help with both the proposal and the qualifications. As a matter of fact I just submitted another manuscript last week, so if all goes well, I’ll get to make one more conference trip before the project is over.

Speaking of other things going on in my life, there is some interesting stuff afoot both on and off duty. In KDD-CHASER, the live trial of our software platform is now underway; deploying the platform has involved working with AWS EC2 virtual servers, which is pretty cool, since I always enjoy a chance to get my hands on technologies I haven’t previously used. Meanwhile, the DCU Campus Choir has started its autumn term, and boy, does it feel great to be singing again! This term we’re apparently doing Vivaldi’s Gloria RV 589 in its entirety, which I’m particularly excited about – it’s a beautiful piece, and also a bit of a challenge that I’m more than happy to accept. Stay tuned for concert dates!

Job security

There’s an old joke about how you can distinguish between theoretical and practical philosophy: if your degree is in practical philosophy, there are practically no jobs available for you, whereas if it’s in theoretical philosophy, it’s not even theoretically possible for you to find a job. I was reminded of this the other day when I was having a lunchtime chat with a colleague who had recently learned of the existence of a vending machine that bakes and dispenses pizzas on request. From this the conversation moved to the broader theme of machines, and particularly artificial intelligence, taking over jobs that previously only humans could perform, such as those that involve designing artefacts.

A specific job that my colleague brought up was architect: how far away are we from the situation where you can just tell an AI to design a building for a given purpose within given parameters and a complete set of plans will come out? This example is interesting, because in architecture – in some architecture at any rate – engineering meets art: the outcome of the process represents a synthesis of practical problem-solving and creative expression, functionality and beauty. Algorithms are good at exploring solution spaces for quantifiable problems, but quantifying the qualities that a work of art is traditionally expected to exhibit is challenging to say the least. Granted, it’s a bit of a cliché, but how exactly does one measure something as abstract as beauty or elegance?

If we follow this train of thought to its logical conclusion, then it would seem that the last jobs to go would be the ones driven entirely by self-expression: painter, sculptor, writer, composer, actor, singer, comedian… Athlete, too – we still want to see humans perform feats of strength, speed and skill even though a robot could easily outdo the best of us at many of them. In a sense, these might be the only jobs that never can be completely taken over by machines, because potentially every human individual has something totally unique to express (unless we eventually give up our individuality altogether and meld into some kind of collective superconsciousness). However, it’s debatable if the concept of a job would any longer have a recognisable meaning in the kind of post-scarcity utopia seemingly implied by this scenario.

Coming back closer to the present day and my own research on collaborative knowledge discovery, I have actually given some (semi-)serious thought to the idea that one day, perhaps in the not-too-far future, some of the partners in your collaboration may be AI agents instead of human experts. As AIs become capable of handling more and more complex tasks independently, the role of humans in the process shifts toward the determination of what tasks need doing in the first place. Applying AI in the future may therefore be less like engineering and more like management, requiring a skill set that’s rather different from the one required today.

So what do managers do? For one thing, they take responsibility for decisions. Why is this relevant? The case of self-driving cars comes to mind. From a purely utilitarian perspective, autopilots should replace human drivers as soon as it can be shown beyond reasonable doubt that they would make roads safer, but while the possibility remains that an autopilot will make a bad call leading to damage or injury, there are other points of view to consider. Being on the road is always a risk, and it seems to me that our acceptance of that risk is at least partially based on an understanding of the behaviour of the other people we share the road with – a kind of informed consent, so to speak. If an increasing percentage of those other people is replaced by AIs whose decision-making processes may differ radically from those of human drivers, does there come a point where we no longer understand the nature of the risk well enough for our consent to be genuinely informed? Would people prefer a risk that’s statistically higher if they feel more confident about their ability to manage it?

On the other side of the responsibility equation there is the question of who is in fact liable when something bad happens. When it’s all humans making the decisions, we have established processes for finding this out, but things get more complicated when there’s algorithmic decision-making involved, and I would assume that the more severe the damage, the less happy people are going to be to accept a conclusion that nobody’s liable because it was the algorithm’s fault and you can’t prosecute an algorithm. In response to these concerns, the concepts of algorithmic transparency and accountability have been introduced, elements of which can already be seen in enacted or proposed legislation such as the GDPR and the U.S. Algorithmic Accountability Act.

This might seem to be pointing toward a rather bleak future where the only “serious” professional role left for humans is taking the blame when something goes wrong, but I’m more hopeful than that. What else do managers do? They set goals, and I would argue that in a human society this is something that only humans can do, no matter how advanced the technology we have at our disposal for pursuing those goals, because it’s a matter of values, not means. Similarly, it’s ultimately determined by human values whether a given course of action, no matter how effective it would be in achieving a goal, is ethically permissible. In science, for example, we may eventually reach a point where an AI, given a research question, is capable of designing experiments, carrying them out and evaluating the results all by itself, but this still leaves vacancies for people whose job it is to decide what questions are worth asking and how far we are willing to go to get the answers.

Perhaps it’s the philosophers who will have the last laugh after all?

Beyond the blue horizon

I’m currently in an in-between state of sorts, waiting to start part two of my summer holiday. One might think that after my action-packed New Zealand adventure the prospect of spending two weeks in Finland would seem rather dull, but as a matter of fact I welcome it wholeheartedly and would gladly extend my stay by another week. However, I also want to spend a decent amount of time back home around Christmas and New Year, so it all comes down to priorities again. At least I’m fairly sure that unlike last summer, this time my vacation won’t be interrupted by a panic involving overdue deliverables, since there are none left to submit until the very end of the project.

When I return to Dublin, it will mark the beginning of the last six months of my two-year fellowship, which I must admit is a slightly terrifying thought. However, the way things are going at the moment is fairly encouraging, with one paper published and the camera-ready version of another one submitted during the past month. Still, I can’t afford to have any illusions regarding the amount of effort it’s going to take to wrap this thing up neatly by the end of January 2020 – I still have the most critical part of the research ahead of me, and I expect it’s not going to be smooth sailing all the way even if there are no actual major setbacks.

Of course I can’t just set the horizon at the end of the fellowship and pretend that there’s nothing beyond it; as tempting as the idea may sometimes seem, there’s no realistic scenario where I’m going to retire at the age of 40, so I need to think about continuity. The basic plan is the same that it’s been all this time – go back to my old research group, at least for a while, assuming that they’re still willing to have me – but the big question, as always, is where the money for my salary is going to come from. In the best case there will be enough short-term funding to see me through to the end of next year, which would provide a nice soft landing but still wouldn’t move the horizon a whole lot further away.

One opportunity I guess I’ll have to take a stab at is the September call of the Academy of Finland, specifically the Academy Research Fellow funding instrument. This would keep me going for another five years, which sounds almost too good to be true, and indeed it more or less is, considering how fierce the competition is. The success rate for these proposals is around ten percent, making the instrument even more competitive than the MSCA Individual Fellowship, where the percentage is around fifteen. It is, of course, encouraging that I did manage to get the MSCA IF, but my past experiences with the AoF have not been so uplifting, so I’m not sure how much I ought to fancy my chances here.

Still, on the whole it looks like this is worth a shot, because I do have a number of things I can build upon as a result of the time I’ve spent here at DCU. These include the concrete results of my research, of course, but also the new skills I’ve learned and the new connections I’ve made. The experience I now have of what makes a successful proposal should also prove valuable, as should the experience of working abroad – in fact, had I stayed at my alma mater, I wouldn’t even be eligible to apply, but thanks to the fellowship, I now pass the Academy’s mobility criterion with flying colours, which is a big part of why I came to Ireland in the first place.

None of this matters, of course, unless I can put together a convincing research plan, and to do that, I first of all need to decide what it is that I want to do research on. Obviously it will be connected to what I’ve been working on in Dublin, but it’s a broad area and there are many different angles from which I could approach it in my future work, so I need to ask myself a couple of questions. One of these is, what would I be really, really interested in doing? Five years is quite a long time to be working on something that you find you’re not that into after all, and it’s hardly a recipe for success in a job that’s pretty much built on the assumption that you’re doing it because you enjoy the challenge and are genuinely curious about what you’re going to discover.

Thankfully, by this point in my life I think I can say I know myself pretty well and have a good idea of the sorts of challenges that will keep me from getting bored. That leaves the other question: what can I successfully argue to the reviewers of my proposal that I am the right guy to attempt? If I’m very lucky, when I draw that Venn diagram it will turn out that the intersection of those two sets contains enough substance to shape a funding-worthy proposal out of, but it’s not exactly a rock solid foundation for my future plans, so I’m going to have to do some hedging of bets. If you have or know a company that could use a creative and computationally minded individual for cool R&D projects, I’d love to hear about it!

New Zealand story

I’m back in Dublin from my two-week expedition to New Zealand, the main reason for which was (ostensibly) to attend the IEEE Congress on Evolutionary Computation in Wellington. I’ve been back since Saturday actually, so by now the worst of the jet lag is behind me and it’s time to do a write-up of my doings and dealings down under. Besides NZ, I had the opportunity to pay a quick visit to Australia as well, since I had a stopover in Sydney that lasted from 6am to 6pm – plenty of time to catch a train from the airport to Circular Quay and snap some smug selfies with the famous opera house prominently in the background.

Having the long break between flights in Sydney proved a good decision, because even though the final hop from Sydney to Wellington was a relatively short one, by this point I had already flown seven and a half hours from Dublin to Dubai, followed by a two-hour stopover before the connecting flight to Sydney, which was just shy of fourteen hours. As a result of all this I wasn’t in much of a mood to do any more flying until I was well and truly rid of the stiffness of body and mind that comes from spending 20-plus hours seated inside a cramped aluminium tube in the sky, and a few hours of sightseeing on foot on what turned out to be a pleasantly warm and sunny day helped a great deal in achieving that. Another move I thanked myself for was having purchased access to the Qantas business lounge at Sydney airport, allowing me to enjoy such welcome luxuries as a comfy chair, a barista-made espresso and a nice shower before facing the world outside.

With the combined effect of the flight and transfer times and the 11-hour time difference, I arrived in Wellington near midnight on the evening of Sunday the 9th, having departed from Dublin on Friday evening. Monday the 10th was the first day of the conference, but it was all tutorials and workshops, none of which were particularly relevant to my own research, so I gave myself permission to sleep in and recharge before attempting anything resembling work. In fact the only “conference sessions” I attended on that first day were lunch and afternoon coffee; the rest of the time I spent at the venue I just wandered around Te Papa, exploring the national museum’s fascinating exhibitions on the nature, culture and history of New Zealand.

On the second day I began to feel the effects of jet lag for real, but I thought it was time to be a good soldier and check out some presentations. Although I don’t really do evolutionary computation myself, it has various applications that interest me professionally or personally, so it wasn’t too hard to find potentially interesting sessions in the programme. The highlight of the day for me was a session on games where there was, among others, a paper on evolving an AI to play a partially observable variant of Ms. Pac-Man; being a bit of a retrogaming geek, I found it quite heartwarming that this is an actual topic of serious academic research!

On the third day I forced myself to get up early enough to hear the plenary talk of Prof. Risto Miikkulainen, titled “Creative AI through Evolutionary Computation”. I was especially looking forward to this talk, and I was not disappointed: Prof. Miikkulainen built a good case for machine creativity as the next big step in AI and for the crucial role of evolutionary computation in it, with a variety of interesting supporting examples of successful applications. I am inclined to agree with the audience member who remarked that the conclusions of the talk were rather optimistic – it’s quite a leap from optimising website designs to optimising the governance of entire societies – but even so, a highly enjoyable presentation. Later that day there was a special session on music, art and creativity, which I also attended, but my enjoyment of it was hampered by my being in acute need of a nap at this point.

The fourth and final day of the conference I mostly spent preparing for my own presentation, which was in the special session on ethics and social implications of computational intelligence. This took place in the late afternoon, so the conference was almost over and attendance in the session was predictably unimpressive: I counted ten people, including myself and the session chair. Fortunately, numbers aren’t everything, and there was some good discussion with the audience after my talk, which dealt with wearable self-tracking devices and the problems that arise from the non-transparency of the information they generate and the limited ability of users to control their own data. I also talked about the problems and potential social impact of analysing self-tracking data collaboratively, tying the paper up with the work I’m doing in the KDD-CHASER project.

After the conference I proceeded to have a week’s vacation in NZ, which of course was the real reason I went to all the trouble of getting myself over there. While it’s not a huge country – somewhat smaller than my native Finland in terms of both area and population – I still had to make some tough choices when deciding what to see and do there, and I came to the conclusion that it was best to focus on what the North Island has to offer. I rode the Northern Explorer train service to Auckland and spent three nights there before working my way back to Wellington by bus, stopping along the way to spend two nights in Rotorua. From Wellington I did a day trip by ferry to Picton, a small town in the Marlborough Region (of Sauvignon blanc fame) of the South Island.

On Friday, two weeks after my departure from Dublin, I started my return journey, this time via Melbourne and with no time to go dilly-dallying outside the airport between flights. I boarded my flight in Wellington feeling a little sad to be leaving NZ so soon, but also satisfied that I’d made the most of my time there. I might have been able to fit in some additional activities if I’d travelled by air instead of overland, perhaps even another city, but I like to be able to view the scenery when I’m travelling, and there was no shortage of pretty sights along the train and bus routes. The conference also left a positive feeling: the programme was interesting, the catering was great and the choice of venue just brilliant. Above all, I’m happy to be done with all the flying!

Collaboration, schmollaboration

Whenever someone asks me what my research project is about, I usually open by saying we’re calling it collaborative knowledge discovery from data. That’s a nice, convenient way of putting it in a nutshell, but it immediately calls for some elaboration, especially on the meaning of the term “collaborative”. Technically, any activity that involves two or more people working together toward a common goal is collaborative, but this definition doesn’t get us very far, because in knowledge discovery you typically have at least someone who knows about the technology and someone who knows about the application domain. It’s not unheard of for one person to know about both, but still, I think it’s safe to say that collaboration is the rule rather than the exception here.

To narrow it down a bit, the kind of collaboration we’re talking about is remote and synchronous. In other words, the participants are not located in the same place, but they can all simultaneously edit whatever it is they’re collaborating on and see the effects of each other’s edits in real time. This implies that there must be some kind of online environment where the collaboration takes place; think something like Google Docs or MS Office Online, only for KDD artifacts such as datasets, algorithms and processing pipelines.

Even this is not a particularly novel idea in itself, as there are collaboration platforms already available where you can develop just these sorts of things. Therefore in KDD-CHASER we’re upping the ante even further by focusing specifically on collaborative knowledge discovery from personal data, driven by the data owner who cannot be assumed to have any particular technology or domain expertise. It’s a bit of a niche, which of course makes our eventual results somewhat less generalisable, but it also makes it considerably easier to spot opportunities for novel research contributions.

To me, the most interesting problems here are not necessarily associated with knowledge discovery as such but with the things that need to happen before knowledge discovery can take place. After all, from the data owner’s perspective the point of collaborating with experts is basically to have the actual discovery done by people who are better equipped for it in terms of skills and tools. This doesn’t mean, however, that the data owner’s role in the collaboration is limited to being a passive data source; on the contrary, it is the data owner’s needs that drive the entire process of collaborative KDD in the special case we’re considering.

The first problem that a data owner may encounter on the way to a successful collaboration is that they don’t even know anyone they could collaborate with, so the first thing the collaboration platform should do is provide a matchmaking service that brings together people who have data with people who have the right sort of expertise to help turn it into something more valuable. After the matchmaking follows the really interesting part: negotiation. What kind of knowledge is the data owner interested in? What is actually achievable, given the available data and the extent to which the data owner is willing to share it with the expert? What is the expert expecting to get in compensation for their efforts? The collaborators need to find the answers to such questions among themselves, and the collaboration platform should support them in this.

The bare minimum is to provide the collaborators with some kind of communication channel, but this is something that would be required anyway, and it’s hardly a research problem from a computing standpoint. However, there’s a lot more to negotiation than just talking, and I’m interested to see what I might do to help things along in this area. Privacy, for example, is traditionally close to my heart and something that I want to address also here, because one of the things to be determined through negotiation is how much of their data the data owner is prepared to trust their collaborators with, considering that the latter may be the KDD equivalent of someone they just matched with on Tinder.

It’s been pretty clear from the start that whatever we manage to accomplish in my current project, it’s not going to be a comprehensive solution to all the problems of collaborative KDD, even within the niche we’ve carved for ourselves. What we can realistically shoot for, though, is a model that shows us what the collaboration process looks like and gives us an understanding of where the major problems are. The software I’m building will basically be a collection of candidate solutions to a select few of these problems, and it will hopefully be something I can continue to build on when my MSCA fellowship is over.

Far side of the world

Things are getting quite busy again, as the project has come to a stage where I need to be producing some publications on early results while also doing implementation work to get more solid results, not to mention thinking seriously about where my next slice of funding is going to come from. Any one of these could consume all of my available time if I allowed it to, and it’s not always easy to motivate yourself to keep pushing when the potential returns are months away at best. What is all too easy, however, is to neglect things that are not strictly necessary – blogging, for example, but I’m determined to write at least one new post each month, even if it’s only because it makes for a welcome respite from the more “serious” work.

One thing that can help a great deal in maintaining motivation is if you have something nice in the not-too-distant future to look forward to, and as it happens, I have quite a biggie: the paper I submitted in January got accepted to the IEEE Congress on Evolutionary Computation, which will be held in Wellington, New Zealand. It’s a bit of a strange event for me to attend; while I do find the field very interesting, my professional experience of it, not counting some courses I took years ago when I was a doctoral student in need of credits, is limited to having been a reviewer for CEC once. However, there is a special session there on the theme of “Ethics and Social Implications of Computational Intelligence”, and this is something I have done actual published work on. It’s also one of the themes I wanted to address in my current project, so that’s that box ticked I guess. Besides, visiting NZ has been on my bucket list for quite a while, so I could hardly pass up the opportunity.

So, a small fraction of my time this month has been spent at the very pleasant task of making travel plans. Wellington lies pretty much literally on the opposite side of the globe from Dublin, so even in this day and age travelling there is something of an operation. It’s not cheap, obviously, but that’s not really a problem, thanks to my rather generous MSCA fellowship budget. The main issue is time: the trip takes a minimum of 27 hours one way, and the “quick” option leaves you with precious little time to stretch your legs between flights. I didn’t exactly relish this idea, so I ended up choosing an itinerary that includes a 12-hour stopover in Sydney on the outbound journey. This should give me a chance to take a shower, reset my internal clock and yes, also go have a look at that funny-looking building where they do all the opera.

It would make little sense to go all that way just for a four-day conference, so after CEC I’m going to take some personal time and spend part of my summer holiday travelling around NZ (even though it will be actually winter there). I still want to spend a couple of weeks in Finland as well, so I have to be frugal with my leave days and efficient in how I use my limited time. Therefore I’m going to be mostly confined to the North Island, although I am planning to take a ferry across Cook Strait to Picton and back – the scenery of the Marlborough Sounds is supposed to be pretty epic. On the North Island I’m going to stop in Auckland and Rotorua before coming back to Wellington; between Auckland and Rotorua, the Hobbiton movie set is a must-see for a Tolkien reader and Lord of the Rings film fan such as myself.

As for the conference, I’m very much looking forward to the plenary talk by my countryman Prof. Risto Miikkulainen on “Creative AI through Evolutionary Computation”. The idea of machines being creative is philosophically challenging, which is part of why this talk interests me, but I’m also intrigued by the practical potential. The abstract mentions techy applications such as neural network architecture design, but personally, I’m particularly interested in artistic creativity – in fact, when I was doing those evolutionary computation courses at my alma mater, I toyed with the idea of a genetic algorithm that would serve as a songwriting aid by generating novel chord progressions. Apart from the plenaries, the conference programme is still TBA, but it’s always good to have a chance to meet and exchange views with people from different cultural and professional backgrounds, and since Wellington is apparently the undisputed craft beer capital of NZ, I’m expecting some very pleasant scholarly discussions over pints of the nation’s finest brews.

Getting fit, bit by bit

I’ve been making decent progress on my software, and while it’s no good yet for any kind of data analysis, it can already be used to do a number of things related to the management of datasets and collaborations. I may even unleash the current incarnation upon some unsuspecting human beings soon, but for now, I’m using myself as my first guinea pig, so I’ve started wearing one of the Fitbits I bought myself (or rather, for my project) for Christmas. From the perspective of my research, the reason for this is that I need to capture some sample data so I can get a look at what the data looks like when it’s exported from the Fitbit cloud into a file, but I’m also personally interested in seeing firsthand what’s happened in fitness trackers since the last time I wore one, which was quite a few years ago and then also for research purposes.

Back then I wasn’t hugely impressed, but it seems that by now these gadgets have advanced enough in terms of both functionality and appearance that I would consider buying one of my own. My initial impression of the Fitbit was that it’s quite sleek but not very comfortable; no matter how I wore it, it always felt either too loose or too tight. However, it seems that I either found the sweet spot or simply grew accustomed to it because it doesn’t bother me that much anymore, although most of the time I am still aware that it’s there. I’m probably not wearing it exactly as recommended by the user manual, but I can’t be bothered to be finicky about it.

By tapping on the screen of the device I can scroll through my basic stats: steps, heart rate, distance, energy expenditure and active minutes. More information is available by launching the Fitbit app; this is where I see, for example, how much sleep the device thinks I’ve had. Here I could also log my weight and what I’ve eaten if I were so inclined. Setting up the device and the app so that they can talk to each other takes a bit of time, but after that the device syncs to the app without any problems, at least on Windows. However, for some reason the app refused to acknowledge that I’m wearing the Fitbit on my right wrist rather than my left; this setting I had to make on the website to make it stick. The website is also where I export my data, which is quick and straightforward to do, with a choice between CSV or Excel for the data format.

The accuracy of the data is not really my number one concern, since I’m interested in the process of collaborative data analysis rather than the results of the analysis. However, on a personal note again, it is interesting to make observations on how the feedback I get from the device and the app relates to how I experience those aspects of my life that the feedback is about. For example, I can’t quite escape the impression that the Fitbit is flattering me, considering how consistently I’ve been getting my daily hour or more of activity even though in my own opinion I certainly don’t exercise every day. On the other hand, I do get a fair bit of walking done on a normal working day, including a brisk afternoon walk in the park next to the university campus whenever I can spare the time, so I guess it all adds up to something over the course of the day.

Based on my fairly brief experience, I can already see a few reasons for the rising popularity of wearables such as the Fitbit. Even if the accuracy of the data in terms of absolute values leaves something to hope for, presumably the device is at least reasonably consistent with itself over time, so if there are any rising or falling trends in your performance, they should be visible in the data. To make the product more friendly and fun to use, the developers have used a host of persuasion and gamification techniques; for example, there are various badges to be earned, with quirky names like “Penguin March”, and occasionally the device gets chatty with me, offering suggestions such as “take me for a walk?”. When I reach the daily magic number of ten thousand steps, the Fitbit vibrates a little silent congratulatory fanfare on my wrist.

In terms of what I need to carry out my project, the Fitbit will definitely serve: setting it up, syncing it and exporting the data all seem to work without any big hassle. As for whether I’m going to get one for myself, I would say that it’s now more likely than before that I will get some kind of wearable – not necessarily a Fitbit, but one that will give me the same kind of information anyway. Having this opportunity to try out a few different ones is an unexpected perk of the project that I now suddenly welcome, even though I wasn’t particularly interested in these devices when I was applying for the grant.

Getting engaged

Besides research, one of the things I’m supposed to be doing as a Marie Curie research fellow is learning new things. Of course, that’s a good thing to be doing regardless of what other things you do, but in the case of the fellowship, it’s expected of me by the funder that I spend my time in Dublin doing things that will help me develop myself and my career prospects. I’ve already learned quite a few useful new things through my research work here, but I’ve also attended a number of training courses and workshops on various topics, and last week I had the opportunity to go to a particularly interesting one dealing with engaged research.

I learned about the workshop from the education and public engagement manager of the Insight Centre, who sent me an email about it and recommended that I sign up. I wasn’t previously familiar with the concept of engaged research, but as I was reading the description of the workshop, it soon became clear that it applies to quite a few, perhaps most, of the research projects I’ve been involved in over the course of my career so far. The gist of how this concept is defined is that it describes research where the individuals or organisations for whom the research is relevant are engaged to be involved in it, not merely as recipients of the eventual results but as co-creators of them. In my case the engaged partners have mostly come from industry, but they could also represent the public sector, civil society or the general public.

The workshop was facilitated by people from Campus Engage, a network that aims to “promote civic and community engagement as a core function of Higher Education on the island or Ireland”. Since Finnish universities have had social influence as their so-called third mission (research and education being the first two) for quite a years now, this statement also rings very familiar. A few days before the workshop, we were requested to fill out a survey with questions about our background and what sort of lessons we were particularly hoping to take home, which the facilitators then used to tailor the content to the interests of those attending the training.

A whole day of training can get very boring if it’s not well planned and executed, but there was no such problem here, as the presentations given by the facilitators were interspersed with discussions of our own questions and experiences, as well as small group activities. The latter involved, for example, studying an extract from a research project proposal and coming up with ways to improve it in terms of stakeholder engagement. One of the things I was hoping the training would give me was information and ideas on how to develop the engagement aspect of my own proposals, and this certainly qualified, although strictly speaking it was perhaps more of a cautionary example of how it’s not meant to be done. We did get more constructive planning tools as well, such as the logic model, a way of planning for long-term impact by laying out the path there as a series of if-then relationships starting with an analysis of the current situation.

Another thing about the workshop that I enjoyed was that we discussed some actual real-world cases of community engagement in action. A particularly interesting one was Access Earth, a mobile app that can be used by people with accessibility needs to find and rate hotels and restaurants by criteria such as accessible parking and wide doors. Clearly the key to successful implementation and deployment of such an application is engaging the people who are going to use it, both to get the design right and to collect the data on the accessibility of various places around the world, and one of the facilitators of the workshop has been working on the project as a community engagement advisor. The app is available worldwide, so the potential impact on the lives of people with disabilities is big – an inspiring example of what engagement is in practice and what it can accomplish.